Job Description:
About Kaleris and the Role
As an AIML Software Engineer at Kaleris, you’ll design, build, and maintain production ML systems that power decision-making across logistics and supply chain products. Partner with data scientists and product teams to deliver scalable model training, serving, monitoring, and continuous improvement.
What You’ll Do
- Own end-to-end ML workflows: data ingestion, feature engineering, training, validation, deployment, and observability.
- Implement robust model serving and APIs; ensure reliability, performance, and security.
- Develop simulators/training environments for safe evaluation of model behavior.
- Automate CI/CD pipelines for ML using containers and cloud-native tooling.
- Monitor model health, detect drift, run A/B tests, and support automated retraining.
- Write clean, well-tested code; contribute to requirements, design, and peer reviews.
Minimum Qualifications
- Bachelor’s/Master’s in Computer Science or related field; 2–4 years of ML/software engineering experience.
- Strong Python skills with hands-on experience using scikit-learn, pandas, numpy, and machine learning algorithms.
- Experience with PyTorch or TensorFlow, SQL, and data wrangling at scale.
- Proficiency with Git, unit/integration testing, and CI/CD.
- Experience deploying to Azure/AWS/GCP with Docker and Kubernetes.
Preferred Qualifications
- Reinforcement learning exposure (policy learning, reward design, evaluation) and/or simulation (discrete-event or agent-based).
- Hands-on experience building enterprise applications with Java and Spring Boot.
- Experience with model governance, monitoring, and automated retraining.
- Domain knowledge in logistics/supply chain operations.
- Hands-on experience with serverless functions for model serving and event-driven data processing, such as Knative, Azure Functions, and AWS Lambda (Amazon Lambda).
Why Kaleris
- High-impact ML work at the frontier of decision intelligence for the supply chain.
- Collaborative, global team; clear career progression and technical leadership opportunities.
- Competitive compensation, benefits, and a culture that values inclusion and craftsmanship.
Kaleris is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Skills Required
- Bachelor's or Master's in Computer Science or related field
- 2-4 years of ML or software engineering experience
- Strong Python skills
- Experience with scikit-learn
- Experience with pandas
- Experience with numpy
- Experience with PyTorch or TensorFlow
- SQL and data wrangling at scale
- Proficiency with Git
- Unit and integration testing experience
- CI/CD pipeline experience
- Experience deploying to Azure, AWS, or GCP using Docker and Kubernetes
- Reinforcement learning exposure (policy learning, reward design, evaluation)
- Simulation experience (discrete-event or agent-based)
- Hands-on experience with Java and Spring Boot
- Experience with model governance, monitoring, and automated retraining
- Domain knowledge in logistics/supply chain operations
- Experience with serverless functions and event-driven processing (Knative, Azure Functions, AWS Lambda)
What We Do
Kaleris is a leading provider of cloud-based supply chain execution and visibility technology solutions. Many of the world's largest brands rely on Kaleris to provide mission-critical technology for yard management, transportation management, maintenance and repair operations, terminal operating systems, and ocean carrier and vessel solutions. By consolidating supply chain execution software assets across major nodes and modes, we address the dark spots and data gaps that cause friction and inefficiency in the global supply chain.
